Evaluation of conventional and industry 4.0 manufacturing work design factors for performance based on personal characteristics

Abstract

Performance of workers can be improved by effective design of work. Several work design factors, physiological, psychological, technological, organizational and social, have been identified in research literature. These factors influence the work in different forms, especially in combination with personal characteristics of workers. Manufacturing technologies are also changing with adoption of industry 4.0 practices. The objective of the research was to test whether workers with different personal characteristics had different relationships with work design factors in the conventional setting. The findings for the current conventional setup are extrapolated on an industry 4.0 work design model with important insights and observations. Managerial implications were inferred from the results which indicated age, education and family size as important variables affecting supervision (Mean mu = 4.29) HSE (mu = 4.23), training (mu = 4.35), aptitude (mu = 4.29), pay and welfare (mu = 3.58), job rotation 0 mu = 3.91), feedback 0 mu = 4.47), pace of operations 0 mu = 4.19), in conventional manufacturing. Old, experienced, educated and married workers with children give certain initiatives to management, which should be utilized for better performance in industry 4.0 production work.